Intelligent evaluation of structural safety performance based on multi-source data
The structure of prestressed steel structure is complex,and the safety performance involves various influencing factors,design parameters and mechanical parameters.In order to realize the intelligent evaluation of the safety state of prestressed steel structure,an intelligent evaluation method for the structural safety performance based on multi-source data was proposed.In the research process,the evaluation was divided into two aspects:analysis and prediction of structural safety performance.Firstly,the relationship between multi-source data and structural safety performance was established.D-S evidence theory and BP neural network were used to analyze and predict the structure safety.On this basis,the intelligent evaluation model of structural safety was built by integrating digital twins and the implementation process was formed.Taking the chord-supported beam roof(symmetric structure)as the test object,the change of structural safety performance under temperature was analyzed,and the corresponding safety performance of different design parameters under load was predicted.Through the safety assessment method,the key stress components of the structure and the correlation mechanism between design parameters and mechanical parameters were obtained,which provides the basis for structural safety maintenance.
NETL
NSTL
万方数据
